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Solving Constraints over Floating-Point Numbers

  • C. Michel
  • M. Rueher
  • Y. Lebbah
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2239)

Abstract

This paper introduces a new framework for tackling constraints over the floating-point numbers. An important application area where such solvers are required is program analysis (e.g., structural test case generation, correctness proof of numeric operations). Albeit the floating-point numbers are a finite subset of the real numbers, classical CSP techniques are ineffective due to the huge size of the domains. Relations that hold over the real numbers may not hold over the floating-point numbers. Moreover, constraints that have no solutions over the reals may hold over the floats. Thus, interval-narrowing techniques, which are used in numeric CSP, cannot safely solve constraints systems over the floats. We analyse here the specific properties of the relations over the floats. A CSP over the floats is formally defined. We show how local-consistency filtering algorithms used in interval solvers can be adapted to achieve a safe pruning of such CSP. Finally, we illustrate the capabilities of a CSP over the floats for the generation of test data.

Keywords

Interval Analysis Constraint System Test Case Generation Labelling Process Interval Extension 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • C. Michel
    • 1
  • M. Rueher
    • 1
  • Y. Lebbah
    • 2
  1. 1.I3S-CNRSUniversité de Nice-Sophia AntipolisSophia Antipolis CedexFrance
  2. 2.Département d’InformatiqueUniversité d’Oran Es-Senia, Faculté des SciencesEl-M'NaouarAlgeria

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